Hundreds of millions people are using personal, shared and business-wide content management systems, such as the Evernote service and software created by the Evernote Corporation of Redwood City, Calif., the Microsoft® Office OneNote and many more systems. Content collections supported by such software and online services may contain thousands and even hundreds of thousands of content items (notes, memos, documents, etc.) with widely varying sizes, content types and other parameters. These items are viewed and modified by users in different order, with different frequency and under different circumstances. Routines for accessing items in content collections may include direct scrolling, keyword and natural language search, accessing items by tags, categories, notebooks, browsing interlinked clusters of items with or without indexes and tables of content, and other methods.
Irrespective of specific methods, quick and targeted access to desired content at any given moment, place and situation is important to user productivity and convenience. Search technologies, organizational and user interface features, such as tags, favorites, folders, advanced content sorting, and other functionality provide a significant help in accessing needed content. Contemporary content management systems may expand search to images, audio and video, synonyms, semantic terms, anthologies and language specifics. Navigational methods for tags, tag clouds, lists of favorites, and interlinked clusters of items are constantly progressing and may include multi-dimensional and dynamic data representation, advanced use of touch interfaces and screen estate, etc.
Still, even the most sophisticated search and navigational methods may be insufficient for quickly growing information volumes. Additionally, repetitive searches for the same materials even with saved queries take additional time with every search occurrence. A recent enterprise search study has discovered a significant search gap affecting all categories of workers: 52% of respondents said they could not find the information they were seeking within an acceptable amount of time using their own organization's enterprise search facility. Further analysis has shown that 65% of respondents have defined an overall good search experience as a situation where a particular search takes less than two minutes. However, only 48% of study participants have reported being able to achieve that result in their own organization. In other words, there exists a 17% gap between user expectation of satisfying search experiences and an enterprise search reality. Additionally, about 90% of respondents reported that taking four minutes or more to find the information they want does not constitute a good search experience; yet 27% responded this was the case within their own enterprises. Accordingly limited search efficiency may drive many users to abandoning search as a method of defining immediate views of materials from personal or shared data collections. Analogously, sorting items in a content collection by time, location, size and other parameters may complicate information processing and still fall short of representing content views required by users.
Furthermore, user needs in accessing various materials from content collections (notes, attachments, notebooks, folders, etc.) are driven, on the one hand, by constantly changing work, home and other environments, and on the other hand, by repetitive patterns of user adaptation to such environments. For example, users may need several notes with standard bits of information (a social security number, a driver license number, a passport number or other IDs, a credit card number) every time they visit an official establishment. However, additional pieces of information that they may need could significantly differ depending on whether the users visit a bank or a medical office, are traveling to a place where they have taken family photos and want to recall them or are reviewing materials before a weekly staff meeting. Reflecting dynamic combinations of parameters, different environments and contexts influencing content access requirements and customized content views may be difficult with fixed content settings such as tags or favorite lists, while trying to memorize such combinations of parameters may be cumbersome, tiring, and inefficient and causing frequent updates as user behavior patterns evolve.
Accordingly, it is desirable to develop advanced systems and methods for generating preferred content views depending on context and user viewing history.